Aggregation and Manipulation in Prediction Markets: Effects of Trading Mechanism and Information Distribution

• 成果类型: Article
• 署名作者: Jian, Lian; Sami, Rahul
• 署名单位: University of Southern California; University of Michigan System; University of Michigan
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.1110.1404
• 发表日期: 2012
• 页码: 123-140
• 关键词: prediction markets; experiments; market scoring rule

摘要

We conduct laboratory experiments on variants of market scoring rule prediction markets, under different information distribution patterns, to evaluate the efficiency and speed of information aggregation, as well as test recent theoretical results on manipulative behavior by traders. We find that markets structured to have a fixed sequence of trades exhibit greater accuracy of information aggregation than the typical form that has unstructured trade. In comparing two commonly used mechanisms, we find no significant difference between the performance of the direct probability-report form and the indirect security-trading form of the market scoring rule. In the case of the markets with a structured order, we find evidence supporting the theoretical prediction that information aggregation is slower when information is complementary. In structured markets, the theoretical prediction that there will be more delayed trading in complementary markets is supported, but we find no support for the prediction that there will be more bluffing in complementary markets. However, the theoretical predictions are not borne out in the unstructured markets.